metode one shot case study

Child Care and Early Education Research Connections

Pre-experimental designs.

Pre-experiments are the simplest form of research design. In a pre-experiment either a single group or multiple groups are observed subsequent to some agent or treatment presumed to cause change.

Types of Pre-Experimental Design

One-shot case study design, one-group pretest-posttest design, static-group comparison.

A single group is studied at a single point in time after some treatment that is presumed to have caused change. The carefully studied single instance is compared to general expectations of what the case would have looked like had the treatment not occurred and to other events casually observed. No control or comparison group is employed.

A single case is observed at two time points, one before the treatment and one after the treatment. Changes in the outcome of interest are presumed to be the result of the intervention or treatment. No control or comparison group is employed.

A group that has experienced some treatment is compared with one that has not. Observed differences between the two groups are assumed to be a result of the treatment.

Validity of Results

An important drawback of pre-experimental designs is that they are subject to numerous threats to their  validity . Consequently, it is often difficult or impossible to dismiss rival hypotheses or explanations. Therefore, researchers must exercise extreme caution in interpreting and generalizing the results from pre-experimental studies.

One reason that it is often difficult to assess the validity of studies that employ a pre-experimental design is that they often do not include any control or comparison group. Without something to compare it to, it is difficult to assess the significance of an observed change in the case. The change could be the result of historical changes unrelated to the treatment, the maturation of the subject, or an artifact of the testing.

Even when pre-experimental designs identify a comparison group, it is still difficult to dismiss rival hypotheses for the observed change. This is because there is no formal way to determine whether the two groups would have been the same if it had not been for the treatment. If the treatment group and the comparison group differ after the treatment, this might be a reflection of differences in the initial recruitment to the groups or differential mortality in the experiment.

Advantages and Disadvantages

As exploratory approaches, pre-experiments can be a cost-effective way to discern whether a potential explanation is worthy of further investigation.

Disadvantages

Pre-experiments offer few advantages since it is often difficult or impossible to rule out alternative explanations. The nearly insurmountable threats to their validity are clearly the most important disadvantage of pre-experimental research designs.

One-Group Posttest Only Design: An Introduction

The one-group posttest-only design (a.k.a. one-shot case study ) is a type of quasi-experiment in which the outcome of interest is measured only once after exposing a non-random group of participants to a certain intervention.

The objective is to evaluate the effect of that intervention which can be:

• A training program
• A policy change
• A medical treatment, etc.

As in other quasi-experiments, the group of participants who receive the intervention is selected in a non-random way (for example according to their choosing or that of the researcher).

The one-group posttest-only design is especially characterized by having:

• No control group
• No measurements before the intervention

It is the simplest and weakest of the quasi-experimental designs in terms of level of evidence as the measured outcome cannot be compared to a measurement before the intervention nor to a control group.

So the outcome will be compared to what we assume will happen if the intervention was not implemented. This is generally based on expert knowledge and speculation.

Next we will discuss cases where this design can be useful and its limitations in the study of a causal relationship between the intervention and the outcome.

Advantages and Limitations of the one-group posttest-only design

Advantages of the one-group posttest-only design, 1. advantages related to the non-random selection of participants:.

• Ethical considerations: Random selection of participants is considered unethical when the intervention is believed to be harmful (for example exposing people to smoking or dangerous chemicals) or on the contrary when it is believed to be so beneficial that it would be malevolent not to offer it to all participants (for example a groundbreaking treatment or medical operation).
• Difficulty to adequately randomize subjects and locations: In some cases where the intervention acts on a group of people at a given location, it becomes infeasible to adequately randomize subjects (ex. an intervention that reduces pollution in a given area).

2. Advantages related to the simplicity of this design:

• Feasible with fewer resources than most designs: The one-group posttest-only design is especially useful when the intervention must be quickly introduced and we do not have enough time to take pre-intervention measurements. Other designs may also require a larger sample size or a higher cost to account for the follow-up of a control group.
• No temporality issue: Since the outcome is measured after the intervention, we can be certain that it occurred after it, which is important for inferring a causal relationship between the two.

Limitations of the one-group posttest-only design

1. selection bias:.

Because participants were not chosen at random, it is certainly possible that those who volunteered are not representative of the population of interest on which we intend to draw our conclusions.

2. Limitation due to maturation:

Because we don’t have a control group nor a pre-intervention measurement of the variable of interest, the post-intervention measurement will be compared to what we believe or assume would happen was there no intervention at all.

The problem is when the outcome of interest has a natural fluctuation pattern (maturation effect) that we don’t know about.

So since certain factors are essentially hard to predict and since 1 measurement is certainly not enough to understand the natural pattern of an outcome, therefore with the one-group posttest-only design, we can hardly infer any causal relationship between intervention and outcome.

3. Limitation due to history:

The idea here is that we may have a historical event, which may also influence the outcome, occurring at the same time as the intervention.

The problem is that this event can now be an alternative explanation of the observed outcome. The only way out of this is if the effect of this event on the outcome is well-known and documented in order to account for it in our data analysis.

This is why most of the time we prefer other designs that include a control group (made of people who were exposed to the historical event but not to the intervention) as it provides us with a reference to compare to.

Example of a study that used the one-group posttest-only design

In 2018, Tsai et al. designed an exercise program for older adults based on traditional Chinese medicine ideas, and wanted to test its feasibility, safety and helpfulness.

So they conducted a one-group posttest-only study as a pilot test with 31 older adult volunteers. Then they evaluated these participants (using open-ended questions) after receiving the intervention (the exercise program).

The study concluded that the program was safe, helpful and suitable for older adults.

What can we learn from this example?

1. work within the design limitations:.

Notice that the outcome measured was the feasibility of the program and not its health effects on older adults.

The purpose of the study was to design an exercise program based on the participants’ feedback. So a pilot one-group posttest-only study was enough to do so.

For studying the health effects of this program on older adults a randomized controlled trial will certainly be necessary.

2. Be careful with generalization when working with non-randomly selected participants:

For instance, participants who volunteered to be in this study were all physically active older adults who exercise regularly.

Therefore, the study results may not generalize to all the elderly population.

• Shadish WR, Cook TD, Campbell DT. Experimental and Quasi-Experimental Designs for Generalized Causal Inference . 2nd Edition. Cengage Learning; 2001.
• Campbell DT, Stanley J. Experimental and Quasi-Experimental Designs for Research . 1st Edition. Cengage Learning; 1963.

Further reading

• Understand Quasi-Experimental Design Through an Example
• Experimental vs Quasi-Experimental Design
• Static-Group Comparison Design
• One-Group Pretest-Posttest Design

Academia.edu no longer supports Internet Explorer.

To browse Academia.edu and the wider internet faster and more securely, please take a few seconds to  upgrade your browser .

Enter the email address you signed up with and we'll email you a reset link.

• We're Hiring!
• Help Center

2. The “One Shot” Case Study Revisited

Method. Thousand Oaks, CA: Pine Forge Press.———.(2000). Fuzzy Set Social Science. Chicago, IL: University of Chicago Press. Ragin, Charles C. and Howard Becker, eds.(1992). What Is a Case? Exploring the Foundations of Social Inquiry. Cambridge, UK: Cambridge University Press. Savolainen, Jukka.(1994).“The Rationality of Drawing Big Conclusions Based on Small Samples: In Defense of Mill's Methods.” Social Forces 72 (2), 1217–1224. Stinchcombe, Arthur.(1968). Constructing Social Theories.

Related Papers

Papers Revista De Sociologia

Mihaela Vancea

Journal of Politics

Bear Braumoeller

Papers: revista de sociologia

Erasmus Journal for Philosophy and Economics

Attilia Ruzzene

Mohammed Faruque Uddin

This article exemplifies Yager’s theory of fuzzy logic for interpersonal communication to the area of social research. Taking the dilemma between qualitative and quantitative approaches into the account, there is an anticipation to make a merge between these two. There is an enormous prospect to turn up scientists’ philanthropic innovations if they could use fuzzy logic in social science researches! However, by using fuzzy logic in sociological research there is a great deal of opportunity to study the social facts related to poverty, consumption, employment, intersubjectivity, social capital, environment, gender etc. How can we use Yager’s theory of Fuzzy Logic to analyze the relationship between social capital and labor market partcicpation? From the experiential connection in Bangladesh society, I try to seek this answer using a hypothetical quantification of attributes.

David Collier

Analysts who developed the set-theoretic comparative method (STCM) have formulated admirable goals for researchers who work in the qualitative and multi-method tradition. STCM includes above all Charles Ragin’s innovative approach of Qualitative Comparative Analysis (QCA). However, the analytic tools employed by STCM have in many ways become an obstacle to achieving these goals. For example, the system of fuzzy-set scoring appears to be problematic, poorly matched to a standard under-standing of conceptual structure, and perhaps unnecessary in its present form. Computer simulations suggest that findings suffer from serious problems of stability and validity; and while the choice of simulations that appropriately evaluate the method is a matter of some controversy, the cumulative weight of simulation results raises major concerns about STCM’s algorithms—i.e., its basic, formalized analytic procedures. Questions also arise about the cumbersome formulation of findings in what is often a remarkably large number of causal paths. Relatedly, some scholars question the STCM’s rejection of the parsimonious findings, in the form of “net effects,” routinely reported in other methodological traditions. Regarding applications, readily available software has encouraged publication of dozens of articles that appear to abandon key foundations of the method and rely far too heavily on these algorithms. Finally, STCM appears inattentive to the major, recent rethinking of standards and procedures for causal inference from observational data. These problems raise the concern that the set-theoretic comparative method, as applied and practiced, has become disconnected from the underlying analytic goals that motivated Charles Ragin to create it.

American Journal of Sociology

Edgar Ojeda

Sujay Rao Mandavilli

The Sociological Ninety ten rules that are proposed in this paper, are based on the fundamental premise that various branches of social sciences like sociology, anthropology and economics are human-centric and are therefore inexact, and vary fundamentally from the more precise and exact sciences like physics, chemistry and mathematics which are characterized by precision and exactitude. A high degree of precision and certainty may not therefore manifest themselves in various branches of the social sciences, even if they at times make use of mathematical models or statistical techniques. Therefore, for every postulated rule in most fields in the social sciences, there are likely to be many different exceptions. These may be described as cultural variations and cultural exceptions, and exceptions over time or space. The name 'Ninety ten' is only an easy-to-understand and easy-to-use nomenclature. Real world exceptions to any given observation could be twenty per cent, five per cent, or take on any other value, but the above nomenclature is chosen for convenience. Variations across or within cultures or within or in between socio-cultural groups, socioeconomic groups, occupational groups or any other parameter must be assessed based on the principles that we propose. This may be a basis for splitting up such groups if necessary for further study and evaluation, and the prerogative for this lies with the researcher. Thus, not only rule-based reasoning but also case-based reasoning must be used for various fields in the social sciences. Therefore, a fundamental premise of this paper is that exceptions must be sought actively, as these will lead to better research and hypothesis formulation. Thus, every researcher must think of rules and exceptions to those rules, and this must become a mindset. If exceptions are significant, they may warrant an altogether different line of research. This process will also greatly aid in inductive analysis, nomothetic rule-building and theorization, and play a major role in the 'Globalization of science', particularly social sciences.

Sociological Methods & Research

Charles Ragin , Paul Pennings

RELATED PAPERS

Constantin Ardeleanu

Prachi Londe

IEEE Transactions on Electron Devices

Byungjong Moon

Helene Lainemäe

Trinidad Quijano

Waliu B A B A T U N D E Ogunbamowo

New England Journal of Medicine

Sumathi Swaminathan

Biochemical and Biophysical Research Communications

Nigel Greig

Media Pendidikan Matematika

Nursiya Bito

Dr. Nany Hairunisa

LASER THERAPY

Salile Khandani

HortTechnology

Suzette Galinato

Kassim Omar Dinle

Frontiers in Psychiatry

Eric Achtyes

Research, Society and Development

LUCIANA SANT ANNA

Antonios Roumpakis

Hira Sharif

Nancy López

Mubarik Ahmed

Firdaus Mukhtar

The Journal of Physiology

Astrid Limb

•   We're Hiring!
•   Help Center
• Find new research papers in:
• Health Sciences
• Earth Sciences
• Cognitive Science
• Mathematics
• Computer Science
• Academia ©2024

• Survey Software The world’s leading omnichannel survey software
• Online Survey Tools Create sophisticated surveys with ease.
• Mobile Offline Conduct efficient field surveys.
• Text Analysis
• Close The Loop
• Automated Translations
• NPS Dashboard
• CATI Manage high volume phone surveys efficiently
• Cloud/On-premise Dialer TCPA compliant Cloud & on-premise dialer
• IVR Survey Software Boost productivity with automated call workflows.
• Analytics Analyze survey data with visual dashboards
• Panel Manager Nurture a loyal community of respondents.
• Survey Portal Best-in-class user friendly survey portal.
• Voxco Audience Conduct targeted sample research in hours.

Find the best survey software for you! (Along with a checklist to compare platforms)

Get Buyer’s Guide

• 100+ question types
• Drag-and-drop interface
• Skip logic and branching
• Multi-lingual survey
• Text piping
• Question library
• CSS customization
• White-label surveys
• Customizable ‘Thank You’ page
• Customizable survey theme
• Reminder send-outs
• Survey rewards
• Social media
• Website surveys
• Correlation analysis
• Cross-tabulation analysis
• Trend analysis
• Real-time dashboard
• Customizable report
• Email address validation
• Recaptcha validation
• SSL security

Take a peek at our powerful survey features to design surveys that scale discoveries.

Download feature sheet.

• Hospitality
• Financial Services
• Academic Research
• Customer Experience
• Employee Experience
• Product Experience
• Market Research
• Social Research
• Data Analysis

Explore Voxco 

Need to map Voxco’s features & offerings? We can help!

Watch a Demo 

Download Brochures 

Get a Quote

• NPS Calculator
• CES Calculator
• A/B Testing Calculator
• Margin of Error Calculator
• Sample Size Calculator
• CX Strategy & Management Hub
• Market Research Hub
• Patient Experience Hub
• Employee Experience Hub
• Market Research Guide
• Customer Experience Guide
• The Voxco Guide to Customer Experience
• NPS Knowledge Hub
• Survey Research Guides
• Survey Template Library
• Webinars and Events
• Feature Sheets
• Try a sample survey
• Professional services

Find the best customer experience platform

Uncover customer pain points, analyze feedback and run successful CX programs with the best CX platform for your team.

Get the Guide Now

We’ve been avid users of the Voxco platform now for over 20 years. It gives us the flexibility to routinely enhance our survey toolkit and provides our clients with a more robust dataset and story to tell their clients.

VP Innovation & Strategic Partnerships, The Logit Group

• Client Stories
• Voxco Reviews
• Why Voxco Research?
• Careers at Voxco
• Vulnerabilities and Ethical Hacking

Explore Regional Offices

• Cloud/On-premise Dialer TCPA compliant Cloud on-premise dialer
• Predictive Analytics
• Customer 360
• Customer Loyalty
• Fraud & Risk Management
• AI/ML Enablement Services
• Credit Underwriting

Get Buyer’s Guide

• SMS surveys
• Banking & Financial Services
• Retail Solution
• Risk Management
• Customer Lifecycle Solutions
• Net Promoter Score
• Customer Behaviour Analytics
• Customer Segmentation
• Data Unification

Explore Voxco 

Watch a Demo 

Download Brochures 

• CX Strategy & Management Hub
• Blogs & White papers
• Case Studies

VP Innovation & Strategic Partnerships, The Logit Group

• Why Voxco Intelligence?
• Our clients
• Client stories
• Featuresheets

Pre-experimental Design: Definition, Types & Examples

• October 1, 2021

SHARE THE ARTICLE ON

Experimental research is conducted to analyze and understand the effect of a program or a treatment. There are three types of experimental research designs – pre-experimental designs, true experimental designs, and quasi-experimental designs . 

In this blog, we will be talking about pre-experimental designs. Let’s first explain pre-experimental research. 

What is Pre-experimental Research?

As the name suggests, pre- experimental research happens even before the true experiment starts. This is done to determine the researchers’ intervention on a group of people. This will help them tell if the investment of cost and time for conducting a true experiment is worth a while. Hence, pre-experimental research is a preliminary step to justify the presence of the researcher’s intervention. 

The pre-experimental approach helps give some sort of guarantee that the experiment can be a full-scale successful study. 

What is Pre-experimental Design?

The pre-experimental design includes one or more than one experimental groups to be observed against certain treatments. It is the simplest form of research design that follows the basic steps in experiments. 

The pre-experimental design does not have a comparison group. This means that while a researcher can claim that participants who received certain treatment have experienced a change, they cannot conclude that the change was caused by the treatment itself. 

The research design can still be useful for exploratory research to test the feasibility for further study. 

Let us understand how pre-experimental design is different from the true and quasi-experiments:

The above table tells us pretty much about the working of the pre-experimental designs. So we can say that it is actually to test treatment, and check whether it has the potential to cause a change or not. For the same reasons, it is advised to perform pre-experiments to define the potential of a true experiment.

See Voxco survey software in action with a Free demo.

Types of Pre-experimental Designs

Assuming now you have a better understanding of what the whole pre-experimental design concept is, it is time to move forward and look at its types and their working:

One-shot case study design

• This design practices the treatment of a single group.
• It only takes a single measurement after the experiment.
• A one-shot case study design only analyses post-test results.

The one-shot case study compares the post-test results to the expected results. It makes clear what the result is and how the case would have looked if the treatment wasn’t done. 

A team leader wants to implement a new soft skills program in the firm. The employees can be measured at the end of the first month to see the improvement in their soft skills. The team leader will know the impact of the program on the employees.

One-group pretest-posttest design

• Like the previous one, this design also works on just one experimental group.
• But this one takes two measures into account. 
• A pre-test and a post-test are conducted. 

As the name suggests, it includes one group and conducts pre-test and post-test on it. The pre-test will tell how the group was before they were put under treatment. Whereas post-test determines the changes in the group after the treatment. 

This sounds like a true experiment , but being a pre-experiment design, it does not have any control group. 

Following the previous example, the team leader here will conduct two tests. One before the soft skill program implementation to know the level of employees before they were put through the training. And a post-test to know their status after the training.

Now that he has a frame of reference, he knows exactly how the program helped the employees. 

Static-group comparison

• This compares two experimental groups.
• One group is exposed to the treatment.
• The other group is not exposed to the treatment.
• The difference between the two groups is the result of the experiment.

As the name suggests, it has two groups, which means it involves a control group too. 

In static-group comparison design, the two groups are observed as one goes through the treatment while the other does not. They are then compared to each other to determine the outcome of the treatment.

The team lead decides one group of employees to get the soft skills training while the other group remains as a control group and is not exposed to any program. He then compares both the groups and finds out the treatment group has evolved in their soft skills more than the control group. 

Due to such working, static-group comparison design is generally perceived as a quasi-experimental design too. 

Characteristics of Pre-experimental Designs

In this section, let us point down the characteristics of pre-experimental design:

• Generally uses only one group for treatment which makes observation simple and easy.
• Validates the experiment in the preliminary phase itself. 
• Pre-experimental design tells the researchers how their intervention will affect the whole study. 
• As they are conducted in the beginning, pre-experimental designs give evidence for or against their intervention.
• It does not involve the randomization of the participants. 
• It generally does not involve the control group, but in some cases where there is a need for studying the control group against the treatment group, static-group comparison comes into the picture. 
• The pre-experimental design gives an idea about how the treatment is going to work in case of actual true experiments.  

Validity of results in Pre-experimental Designs

Validity means a level to which data or results reflect the accuracy of reality. And in the case of pre-experimental research design, it is a tough catch. The reason being testing a hypothesis or dissolving a problem can be quite a difficult task, let’s say close to impossible. This being said, researchers find it challenging to generalize the results they got from the pre-experimental design, over the actual experiment. 

As pre-experimental design generally does not have any comparison groups to compete for the results with, that makes it pretty obvious for the researchers to go through the trouble of believing its results. Without comparison, it is hard to tell how significant or valid the result is. Because there is a chance that the result occurred due to some uncalled changes in the treatment, maturation of the group, or is it just sheer chance. 

Let’s say all the above parameters work just in favor of your experiment, you even have a control group to compare it with, but that still leaves us with one problem. And that is what “kind” of groups we get for the true experiments. It is possible that the subjects in your pre-experimental design were a lot different from the subjects you have for the true experiment. If this is the case, even if your treatment is constant, there is still going to be a change in your results. 

Advantages of Pre-experimental Designs

• Cost-effective due to its easy process. 
• Very simple to conduct.
• Efficient to conduct in the natural environment. 
• It is also suitable for beginners. 
• Involves less human intervention. 
• Determines how your treatment is going to affect the true experiment. 

Disadvantages of Pre-experimental Designs

• It is a weak design to determine causal relationships between variables. 
• Does not have any control over the research. 
• Possess a high threat to internal validity. 
• Researchers find it tough to examine the results’ integrity. 
• The absence of a control group makes the results less reliable. 

This sums up the basics of pre-experimental design and how it differs from other experimental research designs. Curious to learn how you can use survey software to conduct your experimental research, book a meeting with us . 

Explore all the survey question types possible on Voxco

Pre-experimental design is a research method that happens before the true experiment and determines how the researcher’s intervention will affect the experiment.

An example of a pre-experimental design would be a gym trainer implementing a new training schedule for a trainee.

Characteristics of pre-experimental design include its ability to determine the significance of treatment even before the true experiment is performed.

Researchers want to know how their intervention is going to affect the experiment. So even before the true experiment starts, they carry out a pre-experimental research design to determine the possible results of the true experiment.

The pre-experimental design deals with the treatment’s effect on the experiment and is carried out even before the true experiment takes place. While a true experiment is an actual experiment, it is important to conduct its pre-experiment first to see how the intervention is going to affect the experiment.

The true experimental design carries out the pre-test and post-test on both the treatment group as well as a control group. whereas in pre-experimental design, control group and pre-test are options. it does not always have the presence of those two and helps the researcher determine how the real experiment is going to happen.

The main difference between a pre-experimental design and a quasi-experimental design is that pre-experimental design does not use control groups and quasi-experimental design does. Quasi always makes use of the pre-test post-test model of result comparison while pre-experimental design mostly doesn’t.

Non-experimental research methods majorly fall into three categories namely: Cross-sectional research, correlational research and observational research.

Explore Voxco Survey Software

+ Omnichannel Survey Software 

+ Online Survey Software 

+ CATI Survey Software 

+ IVR Survey Software 

+ Market Research Tool

+ Customer Experience Tool 

+ Product Experience Software 

+ Enterprise Survey Software 

Uncover The Power of CSAT Survey Tools And Transform Your CX Strategy

Uncover The Power of CSAT Survey Tools And Transform Your CX Strategy SHARE THE ARTICLE ON Table of Contents Companies build business success on customer

Master the Art of Customer Retention in 2023: 8 Powerful Strategies to Reduce Churn and Keep Your Customers Happy

Master the Art of Customer Retention in 2024: 8 Powerful Strategies to Reduce Churn and Keep Your Customers Happy SHARE THE ARTICLE ON Table of

Voice of the customer financial services

Voice of the customer financial services SHARE THE ARTICLE ON Table of Contents It isn’t a surprise how the voice of customers has been helping

The value in Customer Experience Optimization (and the cost of ignoring it!)

CUSTOMER EXPERIENCE The value in Customer Experience Optimization (and the cost of ignoring it!) LISTEN TO THE ARTICLE Voxco · The Value In Customer Experience

Market Research vs Marketing Research

Market research vs marketing research SHARE THE ARTICLE ON Share on facebook Share on twitter Share on linkedin Table of Contents A research study is

Market research: Definition, types, steps and benefits

Mastering Market Research: Types, Steps, and Benefits SHARE THE ARTICLE ON Table of Contents Market research is an indispensable tool for businesses seeking to navigate

We use cookies in our website to give you the best browsing experience and to tailor advertising. By continuing to use our website, you give us consent to the use of cookies. Read More

• Profil Usaha
• Daftar Menerbitkan Buku
• Kirim Naskah
• Cek Progess Buku
• Cek Royalti Buku
• Kerjasama Net Promoter
• Jasa Parafrase
• Jasa Pengurusan HAKI
• Konsultasi Menulis
• Kerjasama Workshop
• Program Reseller
• Promo Khusus Penulis Deepublish
• Dasar Menulis
• Cara Menerbitkan Buku
• Memasarkan Buku
• Teknik Menulis
• Writing Advice
• Writing Tools
• (NEW 2024) Panduan Menulis Buku Ajar Sesuai RPS
• (NEW 2024) Kunci Sukses Publikasi
• (NEW 2024) Menulis dengan Etika untuk Hindari Plagiarisme
• (PREMIUM) Cara Praktis Menulis Buku
• (NEW) Sukses Menulis Buku Referensi
• (NEW) Panduan Ringkas Menulis Buku Monograf
• Panduan Menulis Buku Ajar (Versi Cepat Paham)
• Rahasia Menulis Buku Ajar
• Self Publishing
• Pedoman Menulis Buku Tanpa Plagiarisme

Home » Desain Penelitian: Pengertian, Jenis, dan Contoh

Desain Penelitian: Pengertian, Jenis, dan Contoh

• Maret 30, 2023
• No Comments

Agar penelitian bisa berjalan sesuai dengan pedoman dan tidak menyimpang, maka desain penelitian merupakan salah satu strategi yang bisa dilakukan. Dengan adanya desain penelitian, tujuan penelitian bisa lebih mudah dicapai

Kita dapat menerapkan desain penelitian mana yang paling cocok digunakan untuk penelitian, baik penelitian kualitatif atau kuantitatif . Pada artikel ini kita akan membahas seputar desain penelitian. Jika kamu mencari informasi yang sama, maka baca artikel selengkapnya! 

Mau menulis buku ajar tapi takut salah? Jadikan panduan ini pedoman dan Anda bisa mulai menulis buku ajar sekarang dengan benar! EBOOK GRATIS! : Panduan Menulis Buku Ajar (Versi Cepat Paham)

Apa Itu Desain Penelitian?

Mari bahas pengertian desain penelitian terlebih dahulu. Desain penelitian adalah rangkaian prosedur dan metode yang dipakai untuk menganalisis dan menghimpun data untuk menentukan variabel yang akan menjadi topik penelitian. 

Desain penelitian juga didefinisikan sebagai strategi yang dilakukan peneliti untuk menghubungkan setiap elemen penelitian dengan sistematis sehingga dalam menganalisis dan menentukan fokus penelitian menjadi lebih efektif dan efisien.

Masalah pada sebuah penelitian akan menentukan jenis apa yang cocok untuk dipilih. Hal tersebut juga menentukan alat dan cara apa yang cocok digunakan untuk mengatasi masalah dalam penelitian.

Desain Penelitian Menurut Para Ahli

Berikut pengertian desain penelitian menurut para ahli:

1. Silaen (2018) 

Menurut Silaen, desain penelitian adalah desain mengenai keseluruhan proses yang diperlukan dalam perencanaan dan pelaksanaan penelitian.

2. Umar (2007)

Menurut para ahli, desain penelitian dapat diartikan sebagai suatu rencana kerja yang terstruktur dalam hal hubungan-hubungan antara variabel secara komprehensif agar hasil risetnya dapat memberikan jawaban atas pertanyaan-pertanyaan riset.

Rencana tersebut mencakup hal-hal yang akan dilakukan preset, mulai dari membuat hipotesis dan implikasinya secara operasional sampai analisis akhir 

3. Nachmias dan Nachmias (1976)

Menurut Nachmias dan Nachmias, desain penelitian merupakan suatu rencana yang membimbing peneliti dalam proses pengumpulan, analisis, dan interpretasi observasi. Maksudnya, suatu model pembuktian logis yang memungkinkan peneliti untuk mengambil inferensi mengenai hubungan kausal antar variabel di dalam suatu penelitian.

4 Jenis Desain Penelitian

Pemilihan jenis desain penelitian didasari oleh tujuan penelitian yang akan dilakukan. Terdapat empat jenis desain penelitian yang kerap digunakan, diantaranya:

1. Desain Penelitian Eksperimental

Sesuai namanya, desain penelitian eksperimental berarti peneliti sedang melakukan penelitian eksperimental. Menurut Arifin (2009:127), penelitian eksperimen diartikan sebagai penelitian yang di dalamnya melibatkan manipulasi terhadap kondisi subjek yang diteliti, disertai upaya kontrol yang ketat terhadap faktor-faktor luar serta melibatkan subjek pembanding atau metode ilmiah yang sistematis yang dilakukan untuk membangun hubungan yang melibatkan fenomena sebab akibat.

Desain penelitian eksperimen ditentukan oleh bagaimana cara peneliti mengatur subjek ke dalam kondisi dan kelompok yang berbeda. Terdapat tiga jenis desain penelitian eksperimen, yaitu pre-eksperimental, quasi-eksperimental, dan true experimental research.

a. Desain Penelitian Pre-eksperimental

Pada desain penelitian pre-eksperimental, baik satu atau berbagai kelompok variabel terikat diamati untuk mengetahui ada tidaknya pengaruh dari aplikasi suatu variabel bebas yang sebelumnya dianggap dapat menyebabkan perubahan. Desain ini merupakan yang desain penelitian eksperimen yang paling sederhana dan tidak terdapat kelompok kontrol. Lebih lanjut lagi, desain pre-eksperimental dibagi menjadi tiga, yaitu:

1) One-shot Case Study Research Design

Dalam penelitian eksperimen jenis ini, hanya ada satu kelompok variabel terikat yang dipertimbangkan. Penelitiannya dilakukan setelah memberikan beberapa perlakuan yang sebelumnya dianggap menimbulkan perubahan, sehingga desain ini merupakan suatu posttest study.

2) One-group Pretest-posttest Research Design

Desain penelitian ini mengkombinasikan posttest dan pretest study dengan mengadakan suatu tes pada satu kelompok sebelum diberi perlakuan dan setelah diberikan perlakuan. Pretest dilakukan pada awal penelitian dan posttest diberikan saat penelitian selesai.

3) Static-group Comparison

Pada desain ini, 2 atau lebih kelompok diberikan pengawasan, dimana hanya ada satu kelompok yang diberi perlakuan. Kelompok sisanya dibiarkan statis tanpa diberi perlakuan khusus. Semua kelompok yang ada kemudian diberikan posttest, kemudian adanya perbedaan yang tampak diantara kelompok-kelompok tersebut diasumsikan sebagai hasil dari perlakuan yang diberikan.

b. Desain Penelitian Quasi-eksperimental

Kata “quasi” memiliki arti parsial, setengah, atau pseudo (palsu). Sehingga penelitian quasi-eksperimental memiliki kemiripan dengan true experimental research, tetapi tidak sama. Pada quasi-eksperimen, partisipan tidak dipilih secara acak, sehingga desain penelitian ini digunakan pada kondisi dimana randomisasi sulit atau tidak mungkin dilakukan.

c. True Experimental Research Design

Desain penelitian ini bergantung pada analisis statistik untuk menerima atau menolak hipotesis. True experimental research design merupakan desain penelitian eksperimen yang paling akurat dan dapat dilakukan dengan atau tanpa pretest pada paling tidak 2 kelompok subjek variabel terikat yang dipilih secara acak.

True experimental research design harus memiliki kelompok kontrol, variabel yang dapat dimanipulasi oleh peneliti, dan distribusinya harus secara acak atau random. Klasifikasi dari true experimental research design meliputi:

1) The Posttest-only Control Group Design

Desain ini memilih subjek secara acak atau random dan dikelompokkan menjadi 2 kelompok (kontrol dan eksperimental), dan hanya kelompok eksperimental yang diberi perlakuan. Setelah observasi mendalam, kedua kelompok diberi post-test, dan suatu kesimpulan diambil dari perbedaan yang terjadi di antara kedua kelompok.

2) The Pretest-posttest Control Group Design

Pada desain kelompok kontrol ini, subjek dipilih dan dibagi menjadi 2 kelompok secara acak, kemudian kedua kelompok diberi pretest, namun hanya kelompok eksperimental yang diberikan perlakuan. Di akhir penelitian, kedua kelompok diberi post-test untuk mengukur derajat perubahan di tiap kelompok.

3) Solomon Four-group Design

Desain ini merupakan kombinasi dari pretest-only dan pretest-posttest control groups. Dalam desain ini, subjek yang telah dipilih secara acak atau random ditempatkan menjadi 4 kelompok. Dua kelompok pertama diuji menggunakan metode posttest-only, sementara dua kelompok yang lain diuji menggunakan metode pretest-posttest.

2. Desain Penelitian Survey

Penelitian survei adalah penelitian yang dilakukan pada populasi besar maupun kecil, tetapi data yang dipelajari adalah data dari sampel yang diambil dari populasi tersebut, untuk menemukan kejadian-kejadian relatif, distribusi, dan hubungan-hubungan antar variabel sosiologis maupun psikologis.

Menurut para ahli, terdapat beberapa desain penelitian survey, yaitu desain pembagian silang atau cross sectional design dan desain survey berkepanjangan atau longitudinal survey (Widodo, 2008), sample survey, dan sensus survei (Irawan Soehartono, 2000). Dengan demikian desain penelitian survey di antaranya adalah sebagai berikut.

a. Cross Sectional Survey

Desain penelitian silang atau cross sectional survey digunakan untuk mengetahui isu-isu yang bersifat temporer melalui pengumpulan data yang dilakukan satu kali saja. Desain jenis ini paling banyak digunakan oleh peneliti.

Desain penelitian berkepanjangan atau longitudinal survey digunakan untuk memahami suatu isu secara berkelanjutan. Populasi yang digunakan dalam desain ini tidaklah banyak. Adapun pengambilan data dilakukan secara berkala. Desain jenis ini dibedakan atas kajian kecenderungan atau trend studies, studi panel atau panel studies, sosiometrik, dan desain kontekstual atau contextual design. 

b. Sample Survey

Sample survey adalah survey yang dilakukan pada sebagian populasi atau sampel.

c. Sensus Survey

Sensus survey adalah survey yang dilakukan pada seluruh populasi.

3. Desain Penelitian Longitudinal

Penelitian longitudinal merupakan penelitian yang menggunakan data dengan rentang waktu yang panjang. Berapa lamakah panjang waktu yang dimaksud bersifat sangat relatif. Namun, penekanan riset longitudinal sebenarnya pada ekstensi atau perpanjangan dari survey yang dilakukan. Perpanjangan tersebut bersifat periodik.

Jadi, penelitian longitudinal dapat pula dipahami sebagai perpanjangan penelitian survey yang bersifat periodik. Sedikitnya, survey dilakukan dua kali dengan rentang waktu yang ditentukan dari awal. Teknik pengumpulan data penelitian ini biasanya menggunakan kuesioner atau interview terstruktur. 

Desain penelitiannya pun tidak jauh berbeda dengan penelitian lain seperti survey. Sebagai contoh, kita akan melakukan penelitian tentang perubahan karakteristik kekerasan pemuda di suatu kota yang kerap terjadi tawuran.

Untuk melakukan riset longitudinal, pertama-tama kita melakukan survey dengan kuesioner dan atau wawancara terhadap anak muda yang terpilih sebagai sampel. Identitas partisipan atau anak muda tersebut kita catat baik-baik dan disimpan dengan rapi di dalam arsip. Survey pertama dilakukan dengan variabel yang telah disusun matang.

Riset ini menggunakan rentang waktu yang jelas. Misalnya, setiap lima tahun kita mendatangi anak muda yang sama untuk dilihat perubahan atau perkembangan dalam karakteristiknya. Tak ada ketentuan berapa kali partisipan didatangi kembali untuk disurvey, namun biasanya sedikitnya dua kali mereka disurvey kembali.

Hasil survei kedua, ketiga dan seterusnya akan memperlihatkan perubahan apa yang terjadi pada anak muda tersebut yang barangkali di survey yang ketiga dan seterusnya bukan lagi tergolong anak muda. Dengan desain penelitian ini, perubahan karakteristik kekerasan sebagaimana yang menjadi fokus penelitian sangat mungkin diketahui.

4. Desain Penelitian Studi Kasus

Studi kasus menjadi metode paling sesuai untuk fase penyelidikan dari sebuah penelitian karena mengedepankan survey dan proses historis sebagai jalan untuk penjelasan yang bersifat sebab musabab (kausalitas). Meskipun demikian, metode studi kasus hanya merupakan persiapan metode penelitian dan tidak dapat digunakan untuk menggambarkan atau menguji suatu masalah.

Kriteria penetapan desain penelitian studi kasus sangat berpengaruh terhadap suatu penelitian. Demikian juga untuk penelitian studi kasus. Kriteria kualitas desain penelitian berkaitan dengan:

• Validitas konstruk yakni menetapkan ukuran operasional yang benar untuk konsep-konsep yang akan diteliti. Dalam studi kasus, dapat digunakan teknik multi sumber bukti, memberikan kesempatan kepada informan kunci untuk meninjau kembali draft laporan studi kasus yang bersangkutan.
• Validitas internal merupakan hubungan sebab-akibat, dimana kondisi-kondisi tertentu diperhatikan guna mengarahkan kondisi-kondisi lain, untuk membedakan dari hubungan semu.
• Validitas eksternal yaitu menetapkan ranah dimana temuan suatu penelitian dapat divisualisasikan.
• Reliabilitas  yaitu bahwa suatu penelitian seperti prosedur pengumpulan data dapat diinterpretasikan dengan hasil yang sama pada waktu yang berbeda.
• Desain penelitian komparatif

Menurut Menurut Robert K. Yin, desain penelitian studi kasus secara umum menjadi 2 (dua) jenis, yaitu penelitian studi kasus dengan menggunakan kasus tunggal dan jamak/ banyak. Disamping itu, ia juga mengelompokkannya berdasarkan jumlah unit analisisnya, yaitu (1) penelitian studi kasus tunggal holistik (holistic) yang menggunakan satu unit analisis.(2) Desain kasus tunggal terjalin (embedded) yang menggunakan beberapa atau banyak unit analisis. 

Penelitian studi kasus disebut terpancang (embedded), karena terikat (terpancang) pada unit-unit analisisnya yang telah ditentukan. Perbedaan antara penelitian studi kasus holistik (jenis 1) dan terpancang (jenis 2) adalah pada jumlah unit analisis yang digunakan.

Contoh Desain Penelitian

1. penelitian kualitatif.

Penelitian deskriptif kualitatif ditujukan untuk mendeskripsikan dan menggambarkan fenomena-fenomena yang ada, baik bersifat alamiah maupun rekayasa manusia, yang lebih memperhatikan mengenai karakteristik, kualitas, keterkaitan antar kegiatan. Selain itu, Penelitian deskriptif tidak memberikan perlakuan, manipulasi atau pengubahan pada variabel-variabel yang diteliti, melainkan menggambarkan suatu kondisi yang apa adanya. 

Seperti contoh penelitian sebagai berikut ini: 

Judul penelitian: Mengeksplor fenomena kejujuran di SD Negeri 3 Purwodadi, Kabupaten Banyumas

Satu-satunya perlakuan yang diberikan hanyalah penelitian itu sendiri, yang dilakukan melalui observasi, wawancara, dan dokumentasi. Berdasarkan keterangan dari beberapa ahli di atas, dapat ditarik kesimpulan bahwa penelitian deskriptif kualitatif yaitu rangkaian kegiatan untuk memperoleh data yang bersifat apa adanya tanpa ada dalam kondisi tertentu yang hasilnya lebih menekankan makna. Di sini, peneliti menggunakan metode penelitian deskriptif kualitatif karena penelitian ini

mengeksplor fenomena proses pembentukan karakter peserta didik melalui penyelenggaraan kantin kejujuran di SD Negeri 3 Purwodadi Kecamatan Tambak Kabupaten Banyumas. Selain itu penelitian ini juga bersifat induktif dan hasilnya lebih menekankan makna.

2. Penelitian Eksperimen

Eksperimen dalam penelitian sosial sering digunakan untuk menemukan aspek penyebab atau penyebab fenomena sosial. Seringkali desain eksperimental digunakan sebagai dasar untuk mengimplementasikan suatu program atau kebijakan.

Misalnya, sebagai contoh sederhana dari penelitian eksperimental, peneliti ingin mengetahui efektivitas penggunaan sistem alarm rokok di ruang publik untuk mengurangi konsumsi rokok di tempat umum. Beberapa ruang publik dibangun menjadi rokok, yang lain dengan fitur yang sama tidak dilengkapi dengan alarm rokok.

Eksperimen ini akan menunjukkan hasil seberapa efektif alarm rokok dapat mengurangi konsumsi rokok di tempat umum.

3. Penelitian Kuantitatif

Desain penelitian kuantitatif membuat proyek eksperimental lebih bebas. Maka peneliti sosial umumnya menerapkan desain eksperimental untuk melakukan penelitian kuantitatif. Penelitian kuantitatif bisa dipergunakan guna membandingkan kelompok yang diperlakukan sebagai subjek eksperimen dan kontrol.

Misalnya, percobaan konsumsi vitamin C untuk meningkatkan daya tahan siswa. Beberapa subjek diminta untuk mengonsumsi vitamin C, yang lain tidak memiliki kelompok kontrol. Hasilnya adalah hasil percobaan.

Dalam pembuatan makalah ilmiah juga ada yang namanya penerapan metode penelitian. Dengan metode penelitian yang bagus, maka makalah ilmiah pun juga bisa terwujud dengan kualitas yang tinggi.

Berbicara mengenai metode penelitian makalah, sebenarnya dalam hal ini sama saja dengan metode yang digunakan pada karya ilmiah secara umum. Termasuk yang sudah disinggung dalam poin sebelumnya. Jadi, di dalamnya bisa menggunakan metode penelitian dengan pendekatan kualitatif maupun kuantitatif. Hanya saja mayoritas contoh makalah menggunakan metode kualitatif.

Selain pendekatan secara umum tersebut, dalam makalah juga biasa menerapkan metode penelitian karya ilmiah pada umumnya. Sebagaimana disebutkan di atas, yakni seperti metode deskriptif dan eksperimen. Jika kasusnya berkaitan dengan fenomena sosial pun bisa mengusung metode penelitian sosial. Dan ketiga metode tersebut selanjutnya akan dibahas secara lebih detail lagi.

Pertanyaan Seputar Desain Penelitian :

Menurut Silaen, desain penelitian adalah desain mengenai keseluruhan proses yang diperlukan dalam perencanaan dan pelaksanaan penelitian. Ketahui definisi desain penelitian menurut para ahli lainnya di artikel ini!

Desain penelitian terdapat 4 jenis, yaitu desain penelitian eksperimental, desain penelitian survey, desain penelitian longitudinal, dan desain penelitian studi kasus. Setiap jenis tersebut terbagi menjadi berbagai jenis lagi. Baca selengkapnya di artikel!

Artikel Terkait:

Instrumen Penelitian

Hipotesis Penelitian 

Pendekatan Penelitian

Responden Penelitian 

Jenis Dat a Penelitian

Tahukah Anda bahwa salah satu cara untuk meningkatkan poin KUM adalah menerbitkan buku. Aturan ini tertuang dalam PO PAK 2019.

Sayangnya, kesibukan dalam mengajar, membuat dosen lupa dengan kewajiban lainnya yaitu mengembangkan karir. Maka dari itu, Penerbit Deepublish hadir untuk membantu para dosen meningkatkan poin KUM dengan menerbitkan buku .

Kunjungi halaman Daftar Menerbitkan Buku , agar konsultan kami dapat segera menghubungi Anda.

Selain itu, kami juga mempunyai E-book Gratis Panduan Menerbitkan Buku yang bisa membantu Anda dalam menyusun buku. Berikut pilihan Ebook Gratis yang bisa Anda dapatkan:

• Download Ebook Gratis : Cara Praktis Menulis Buku (Premium!)
• Download Ebook Gratis : Sukses Menulis Buku Referensi (Baru!)
• Download Ebook Gratis: Strategi Jitu Menulis Buku Monograf (Baru!)
• Download Ebook Gratis: Pedoman Pengisian SISTER (Baru!)
• Download Ebook Gratis: Self Publishing
• Download Ebook Gratis: Rahasia Menulis Buku Ajar
• Download Ebook Gratis: Pedoman Menulis Buku tanpa Plagiarisme
• Download Ebook Gratis: Panduan Menulis Buku Ajar (Versi Cepat Paham)

Mau menulis tapi waktu Anda terbatas?

Gunakan saja layanan parafrase konversi.

Cukup siapkan naskah penelitian (skripsi, tesis, disertasi, artikel ilmiah atau naskah lainnya), kami akan mengonversikan jadi buku yang berpeluang memperoleh nomor ISBN!

Tinggalkan Balasan Batalkan balasan

Alamat email Anda tidak akan dipublikasikan. Ruas yang wajib ditandai *

Simpan nama, email, dan situs web saya pada peramban ini untuk komentar saya berikutnya.

Dapatkan informasi terbaru dari kami seputar promo spesial dan event yang akan datang

Penerbit Deepublish adalah penerbit buku yang memfokuskan penerbitannya dalam bidang pendidikan, pernah meraih penghargaan sebagai Penerbit Terbaik pada Tahun 2017 oleh Perpustakaan Nasional Republik Indonesia (PNRI).

Kritik/Saran Pelayanan  : 0811-  2846 – 130

• Menerbitkan Buku
• Pengadaan Buku
• Reseller Buku
• Mitra Net Promoter

Alamat Kantor

Jl.Rajawali G. Elang 6 No 3 RT/RW 005/033, Drono, Sardonoharjo, Ngaglik, Sleman, D.I Yogyakarta 55581

Telp/Fax kantor : (0274) 283-6082

E1 Marketing : [email protected] E2 Marketing : [email protected]